Financial crises can be predicted — and avoided
Artificial intelligence helps salespeople get back to what they do best — selling
They're called salespeople, but they spend shockingly little of their time selling. Instead, their days consist of administrative work, manual data entry, looking for potential customers and communicating with those prospects: cold calling, sending emails, scheduling meetings and having conversations - many of which lead to nothing.
This is both time-consuming and expensive for companies. Lost sales productivity and wasted marketing budgets cost organizations $1 trillion dollars a year, according to industry estimates.
Things are starting to shift, however. New tools, including ones that incorporate artificial intelligence (AI) - mostly machine learning and natural language processing - are changing the ways in which salespeople do their day-to-day jobs.
For all the talk about how AI is revolutionizing the business-to-business (B2B) sales process, its biggest advantage is more mundane: It is helping salespeople better manage their time.
AI is a transformative technology. Its power lies in its ability to extract, parse and analyze massive amounts of data almost instantly. In a sales context, AI-enabled tools help B2B marketers gain a more nuanced understanding of their customers' wants and needs and improve efficiencies like never before.
According to research from McKinsey & Company, organizations that use AI in sales cite an increase in leads and appointments of more than 50 percent, cost reductions of 40-60 percent and call time reductions of 60-70 percent.
Interestingly, the most innovative tools are also the most practical. Today's AI-powered software does everything from write emails to schedule meetings to detect sales behavior. This helps salespeople identify viable leads and close more deals.
Take, for instance, chatbots. Chatbots use AI to conduct conversations via video, audio or text. Chatbots begin the sales process by asking customers basic questions related to their role, industry and company size.
These low-level questions weed out those who may not meet the minimum qualifications of a company's prospect profile. No salesperson wants to waste time in a conversation that's not going anywhere.
Chatbots and lead scoring machine learning tools further improve and enhance the sales process. Lead scoring determines the worthiness of potential customers by attaching values to them based on their interest in a given set of products or services.
Scores not only help salespeople spot potential customers more quickly, they also help salespeople customize their pitches by mapping out an individual prospect's needs.
That's not all. Virtual sales assistants and chatbots can arrange meetings and calls, which drastically reduce the amount of back-and-forth scheduling details that often swamp salespeople.
Intelligent predictive engagement tools are another illustration. These AI-powered tools remind salespeople to reach out to prospective customers and even recommend what to say during that follow-up call or email. After all, the key to any follow-up with a client is relevant and meaningful content.
Finally, there's process automation. Automation, along with predictive analytics, helps identify relationships between pieces of data. This allows salespeople to develop a deeper understanding of customer behavior and helps them forecast future sales more accurately.
Prescriptive analytics, meanwhile, helps salespeople navigate the sales process by uncovering the best path to value for customers, according to a recent research report by Gartner. Put simply, it enables salespeople to adapt and customize their product recommendations based on their customers' individual needs.
These AI-powered tools are geared at improving sales productivity. They eliminate tedious busywork, such as logging calls or taking notes, and allow salespeople to focus on the essential parts of their job.
Importantly, they empower salespeople to engage with customers who are most apt to buy their products and services.
To be sure, just because these new tools exist does not mean that salespeople will embrace them. Case in point: A large number of customer relationship management (CRM) implementations fail because salespeople do not want to use their time doing data entry. (They, understandably, prefer to spend their time selling.)
However, these data inputs are vital to helping salespeople derive value from CRM by generating the kinds of insights necessary to improve their product's attractiveness in the market and increase sales. To realize the value of CRM systems, salespeople need to be persuaded that adopting them is worthwhile.
There's the rub: Given the biggest constraint for salespeople is the availability of "precious selling time," organizations need to show salespeople that AI implementations can help reallocate their time toward selling. This provides the best opportunity to prevent AI tools from going the way of CRM systems.
But it's likely that salespeople will need convincing. The value proposition is clear: Adopting AI tools will give them their time back.
Zoran Latinovic is a visiting postdoctoral scientist at MIT Sloan School of Management. Sharmila C. Chatterjee is a senior lecturer in marketing and the academic head for the Enterprise Management Track at the school.